Accelerate multi-thread path-dependent digital image correlation by minimizing thread competition for real-time deformation measurement

With the increasing demands on the real-time measurement using digital image correlation (DIC), the fast and ultra-fast computation are attracting much more attention from academic and engineering fields in last decades. Multi-thread parallelization is a recognized effective method to raise the correlation speed of traditional single-thread DIC up to higher order of magnitude. However, for the path-dependent parallel DIC based on specific initial guess propagation method, competition between different threads greatly cuts down the overall speed, because different threads visit the same queue or status matrix at the same time. Therefore, the desired linear speed-up ratio growth could hardly be achieved especially for large thread number. In this work, three novel strategies are proposed to minimize the thread competition for the existing path-dependent parallel DIC, including i) allocating private queues for private thread, ii) restarting idle thread if others are busy, and iii) collecting more uncorrelated neighboring points for subsequent correlation. In this way, the conflict between threads is obviously decreased and experiment results reveal that the proposed method could upgrade the 2D-DIC speed up to 145,000 points per second using 48 threads, which makes the real-time measurement feasible for region of interest (ROI) with less than 5000 points.